Sabermetric Statistic- Runs Scored

Here's a small sabermetric that deals a lot with probability and how many runs a team usually would have gotten in an inning.

Definition- Estimating the number of runs a team “should” have scored given their component offensive statistics, as well as the number of runs a hitter/pitcher/creates/allows.

Many different versions have been used, but most take the form:

A*B/(B+C) + D

A represents baserunners

B represents advancement of baserunners

C represents outs

D represents guaranteed runs (usually just home runs)

In theory, the true identity of the equation is:

Baserunners* (% Baserunners that score) + homeruns.

Different uses:

A = H + W - HR
B = (1.4*TB - .6*H - 3*HR + .1*W)*1.02
C = AB - H
D = HR

A second formula incorporated all of the official offensive statistics with the exception of sacrifices:

A = H + W + HBP - HR - .5*IW
B = (1.4*TB - .6*H - 3*HR + .1*(W + HBP - IW) + .9*(SB - CS - GDP))*1.1
C = AB - H + CS + GDP
D = HR

A third formula was designed to be used with pitching statistics:
A = H + W - HR
B = (1.4*TBe - .6*H - 3*HR + .1*W)*1.1
C = 3*IP
D = HR
Where TBe = 1.12*H + 4*HR

It's more of a probability of how many runs a team would get. For example, if there are men on second and third with nobody out, the probability of scoring 1 run is very high, and scoring 2 runs pretty high as well. Scoring no runs is low, but can happen, and that's where Runs Scored comes in to show the deviation.

The St. Louis Cardinals and Detroit Tigers, two favorites for winning their respectful pennants, would have high runs scored because they get men on base and they are great with runners in scoring position.

Read "The Book: Playing the Percentages in Baseball" by Tom Tango, Mitchel Litchman, and Andrew Dolphin. It has a lot to talk about probability of scoring runs in a given inning.

 Email me at
statsbuddy42@gmail.com with any questions/comments/concerns.



-Evan Boyd